LogNormalVaRPlot2DCL function

Plots log normal VaR against confidence level

Plots the VaR of a portfolio against confidence level assuming that geometric returns are normally distributed, for specified confidence level and holding period.

LogNormalVaRPlot2DCL(...)

Arguments

• ...: The input arguments contain either return data or else mean and standard deviation data. Accordingly, number of input arguments is either 4 or 5. In case there are 4 input arguments, the mean and standard deviation of data is computed from return data. See examples for details.

  returns Vector of daily geometric return data

  mu Mean of daily geometric return data

  sigma Standard deviation of daily geometric return data

  investment Size of investment

  cl VaR confidence level and must be a vector

  hp VaR holding period and must be a scalar

Examples

# Plots VaR against confidene level given geometric return data
   data <- runif(5, min = 0, max = .2)
   LogNormalVaRPlot2DCL(returns = data, investment = 5, cl = seq(.85,.99,.01), hp = 60)

   # Computes VaR against confidence level given mean and standard deviation of return data
   LogNormalVaRPlot2DCL(mu = .012, sigma = .03, investment = 5, cl = seq(.85,.99,.01), hp = 40)

Author(s)

Dinesh Acharya

References

Dowd, K. Measuring Market Risk, Wiley, 2007.